Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

2019

Subfields: Natural Language Processing, Evaluation & Benchmarks

Citations in the corpus

• Visualisation and 'diagnostic classifiers' reveal how recurrent and recursive neural networks process hierarchical structure (2017, neutral): “As we argue in the full paper, neither theoretical results [Siegelmann and Sontag, 1995], nor handcrafted examples [Gers and Schmidhuber, 2001; Rodriguez, 2001], nor large-scale NLP applications [Sutskever et al., 2014; Bahdanau et al., 2015; Kalchbrenner et al., 2014; Socher et al., 2013; Le and Zu”
• The Factual Inconsistency Problem in Abstractive Text Summarization: A Survey (2021, unknown): “In fixed schema extraction, a relation is predicted Metric Category Summarization Dataset Code Goodrich et al. [2019] Triple-based Wikipedia Falke et al. [2019] Textual-Entailment-based CNN/DM Mishra et al. [2020] Textual-Entailment-based CNN/DM QAGS [Wang et al. , 2020] QA-based CNN/DM, XSum FEQA [D”
• Textbooks Are All You Need II: phi-1.5 technical report (2023, methodology): “We use the harness-eval zero-shot accuracy on PIQA, Hellaswag, OpenbookQA, 2-shot performance on MMLU, and exact match score on SQUAD.”
• A systematic review of Green AI (2023, background): “The iconic paper by Strubell et al. (2019) analyzes the carbon impact of The goal of this research can be directly translated into a research question (RQ), which states as follows: RQ: What are the characteristics of Green AI state-of-the-art research?”
• Attention mechanism in neural networks: where it comes and where it goes (2022, background): “Adaptive attention span Adaptive attention span is proposed as an alternative to self-attention [110].”
• Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions (2022, background): “There has been very little development done in this area [75].”